August 2, 2014 | Written by: Abhishek Kaul
Share this post:
“Can you promise product availability now?” is a question asked by most customers. Ability of a company to answer that question is based on how the company is able to build and operate its supply chain. Supply chain encompasses the planning, management of all activities involved in sourcing, procurement, conversion, and logistics. Goal of supply chain is to provide the product on time at location at minimum cost while maintaining desired service levels. With globalization, multiple sourcing, complex partner relationships, increased volatility in demand supply chains have to become more adaptable, agile and aligned.
Most supply chains use forecasting as a way to predict future demand
A degree of demand predictability is achieved using sophisticated forecasting models and local sales manager insights. The task becomes more challenging with growing product variety and proliferation of SKUs. Every organization wants to provide more options to their customers with smaller lot sizes and shorter delivery lead times. Product categorization linked with safety stock and stocking policy will certainly help companies to reduce cost and improve service levels.
Let’s understand how a leading automotive component manufacturer laid down principles for supply chain operations. They categorized the products on quantity and volume using ABC analysis. By analysis of data it was evident that the forecast accuracy (including Mean Absolute Percentage Error [MAPE] and Mean Absolute Deviation [MAD]) was higher for the A category and lower for other categories. Thus the company mandated forecast of A category products by sales managers at each sales office and aggregate this forecast to a national level. Other categories were forecasted at a national level and disaggregated to the sales office level. The company also took a decision to push category A products to sales offices and keep category B products at central warehouses for demand pull. Safety stock for category B products was also kept centrally.
But as many people say forecast is always wrong. If we accept that fact and plan only for customer orders then we service customers with long lead times (transportation plus manufacturing plus procurement lead time – assuming no inventory stocking). Companies use a mix of make to order, make to stock and finish to order policies to buffer against the uncertain demand forecast and keep lower inventories.
Let us take a case example from an integrated steel manufacture on perfect product availability – based on the philosophy of allocation planning with decoupling points (order penetration point). Traditionally steel manufactures have used allocation planning as a way to promise order availability. These allocations are based on forecast for aggregated (planning) products and adjusted for customer priority, mill productivity constraints, and to maximize contribution of product mix. In this example we discuss the ability of a steel company to offer shorter lead times, produce semi-finished inventory to forecast and finish to order specification.
Let us say we have two operations OP1 and OP2 taking 7 days each. OP 1 is has a lot size of 100 tons and OP2 has a lot size of 20 tons. Only grade specification are required for OP1. Thickness & color specification are required for OP2. Forecast for multiple finished products is clubbed together on semi-finished product specification ie grade and operation OP 1 is executed. Now stock is available at decoupling point. Based on customer order specification – thickness and color semi-finished stock is processed further through operation OP2. This allows the company to reduce overall lead time by 7 days, be flexible on smaller lots, reduce finished inventory surplus due to forecast error.
This example illustrates how we segment the supply chain between make to order and make to stock strategies in order to manage infinite variation of steel industries end products, service smaller lot sizes on shorter lead times.
Let us take another case example from industrial component manufacturer on perfect product availability – based on the philosophy of capable to promise planning. Traditionally lead time for procurement, manufacturing and transportation dictate overall product lead time. In this example we discuss ability of the company to change product mix within lead time, to keep customer order promise date, provide availability of product mix to full available capacity, constantly prioritize order book to overwrite forecasted product mix at each stage (procurement step, operation execution, transportation leg).
Let us say we have two products P1 and P2. These are made using the same raw material RM1. Raw material procurement time 10 days. Two operations are required OP1 and OP2 to convert raw material to finished goods. OP1 is common to P1 and P2 – takes 5 days. OP2 is different for P1 and P2 – takes 5 days. Thus our product lead time for P1 or P2 is (10+5+5) equal to 20 days. We forecast for P1 and P2 – say 50 for P1 and 50 for P2. Based on that we place raw material order for RM1 summing the demands of P1 and P2 –100 nos. Now we have planned availability of 100 nos for both the products to customer. We get an order for say 80 nos for P1. This order loads the resources and we have remaining availability of P1 or P2 for 20nos. We execute operation OP 1 for 100 nos. Once we reach 5 days before production finish, we take an informed decision on product mix between P1 and P2. We plan 80 nos of P1 on operation OP2 prioritizing order received (overwriting forecast). Now for the remaining 20 we distribute between P1 & P2 based on near term 5 days future forecast.
This example illustrates how we reduce forecasting error by taking product mix decision as late as possible and within overall product lead time. Now let us extend this concept to the entire supply chain network. We plan based on forecast, however only when lead times are due, ie transportation leg lead time, operation lead time (single operation in manufacturing), procurement lead time we take a decision to correct product mix based on current situation of order book and near term forecast. This allows us to have perfect availability even with large product variants, low inventory and entire capacity available to customers for product mix .
Perfect product availability is supported by design and operation of supply chain
It is the hidden mantra for successful manufacturing companies. Supply chain innovation goals must be constantly elevated; supported by adaptation and application of the latest state of the art technologies.
For more information about our metals and mining solutions, technology and consulting, visit our website.